Evidence map›Paper›PMID 38899534›Full record

ArticleCancer medicine2024

Discriminating atypical parotid carcinoma and pleomorphic adenoma utilizing extracellular volume fraction and arterial enhancement fraction derived from contrast-enhanced CT imaging: A multicenter study.

Zhen-Yu Xu, Lin-Wen Huang, Yun-Jun Yang, Zhi-Ping Cai, Mei-Lin Chen, Rui-Liang Lu, Yong-Xi Ouyang, Zhen-Kai Hong, Wei-Jun Huang, Zhi-Feng Xu

Abstract readMulticenter Study
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Zhen-Yu XuDepartment of Radiology, The First People's Hospital of Foshan, Foshan, China.
Lin-Wen HuangDepartment of Radiology, The First People's Hospital of Foshan, Foshan, China.
Yun-Jun YangDepartment of Radiology, The First People's Hospital of Foshan, Foshan, China.
Zhi-Ping CaiDepartment of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde), Foshan, China.
Mei-Lin ChenDepartment of Radiology, The First People's Hospital of Foshan, Foshan, China.
Rui-Liang LuDepartment of Radiology, The First People's Hospital of Foshan, Foshan, China.
Yong-Xi OuyangDepartment of Radiology, The First People's Hospital of Foshan, Foshan, China.
Zhen-Kai HongDepartment of Radiology, The First People's Hospital of Foshan, Foshan, China.
Wei-Jun HuangDepartment of Ultrasound, The First People's Hospital of Foshan, Foshan, China.
Zhi-Feng XuDepartment of Radiology, The First People's Hospital of Foshan, Foshan, China.ORCID 0000-0002-9198-9031

Funding

Foshan 14th Five-Year Plan Key Discipline Foundation FSGSP145036Foshan Science and Technology Bureau Project 2220001003972The Guangdong Basic and Applied Basic Research Foundation under Grant 2019A1515110976
6 · The paper itself

Abstract

objectivesTo investigate the added value of extracellular volume fraction (ECV) and arterial enhancement fraction (AEF) derived from enhanced CT to conventional image and clinical features for differentiating between pleomorphic adenoma (PA) and atypical parotid adenocarcinoma (PCA) pre-operation.

methodsFrom January 2010 to October 2023, a total of 187 cases of parotid tumors were recruited, and divided into training cohort (102 PAs and 51 PCAs) and testing cohort (24 PAs and 10 atypical PCAs). Clinical and CT image features of tumor were assessed. Both enhanced CT-derived ECV and AEF were calculated. Univariate analysis identified variables with statistically significant differences between the two subgroups in the training cohort. Multivariate logistic regression analysis with the forward variable selection method was used to build four models (clinical model, clinical model+ECV, clinical model+AEF, and combined model). Diagnostic performances were evaluated using receiver operating characteristic (ROC) curve analyses. Delong's test compared model differences, and calibration curve and decision curve analysis (DCA) assessed calibration and clinical application.

resultsAge and boundary were chosen to build clinical model, and to construct its ROC curve. Amalgamating the clinical model, ECV, and AEF to establish a combined model demonstrated superior diagnostic effectiveness compared to the clinical model in both the training and test cohorts (AUC = 0.888, 0.867). There was a significant statistical difference between the combined model and the clinical model in the training cohort (p = 0.0145).

conclusionsECV and AEF are helpful in differentiating PA and atypical PCA, and integrating clinical and CT image features can further improve the diagnostic performance.

Indexed as

Adenoma, PleomorphicContrast MediaParotid NeoplasmsTomography, X-Ray ComputedAdenocarcinomaAdultAgedDiagnosis, DifferentialFemaleHumansMaleMiddle AgedRetrospective StudiesROC CurveContrast Mediaarterial enhancement fractioncomputed tomographyextracellular volume fractionparotid carcinomapleomorphic adenoma

Identifiers

PMID38899534
PMCPMC11187748

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.